This paper explores pedagogical practices and participants’ engagement
in learning activities during the first international Massive Open
Online Course (MOOC) offered by the University of Oslo through the
FutureLearn platform in 2015. The data were collected using pre-
and post-course surveys and participant observations. We used the
acquisition and participation metaphors of learning proposed by
Sfard (1998) as a conceptual framework to inform our analyses and
discussions. The data indicated that new pedagogical practices are
in the making for online learning, involving elements of existing
practices and radically new ones. The instructors had sole authority
in developing and curating course contents, thus following the acquisition
metaphor of teaching and learning. In addition, the data indicated
that, overall, the learners had a positive experience of learning
by participating in the MOOC. The learners engaged in online discussion
forums, interacting asynchronously with fellow learners and mentors.
The discussion forums promoted knowledge sharing and collaborative
learning activities among diverse groups (joiners, surveyors, and social
learners). The apparent contradiction between teaching according
to the acquisition metaphor and the learners’ preferences for the
participation metaphor was resolved by some of the learners through
self-organised scaffolding. The teachers did not interact enough
with the learners and so, to compensate, some learners took on facilitating
roles. We discuss our findings in terms of the related work and
contemporary trends in online learning and higher education research,
including learning analytics, formative assessment, personalization,
collaboration support, and lifelong learning.

Introduction

Rooted in the ideal of openness in education, Massive Open Online
Courses (MOOCs) have become a new instructional trend in higher
education (HE) for engaging a large, diverse group of learners in
online activities. Because of their flexibility, MOOCs have demonstrated
in specific cases the coordinated efforts of “active engagement
of several hundred to several thousands of learners who self-organise
their participation according to their learning goals, prior knowledge
and skills, and common interests” (McAuley et al., 2010, p. 5).
Although the ultimate impact and sustainability of MOOCs are not
yet known, these courses have gained popularity in the higher education
(HE) sector since top universities from around the world began to
embrace this model and to provide these courses free of charge.
Arguably the biggest strength of MOOCs is their flexibility, as
they provide opportunities for learning anytime and anywhere in
formal and informal education, while one of the most frequently
reported drawbacks is that they have high dropout rates (Breslow
et al., 2013; Ho et al., 2014; Jordan, 2014) and require extensive
preparation time. For example, in the MOOC analysed in this paper,
there was a dropout rate of more than 90% of the students and it
had 58 short videos prepared in advance (Singh, 2016).

MOOCs are one of the fastest growing technological developments
in the education sector—they have grown by 10% since the launch
of the first MOOC in 2008 (Toven-Lindsey, Rhoads & Lozano, 2015)—and
offering a MOOC has been a matter of reputation and way of branding
and marketing for many universities. MOOCs may prove to be an integral part
of HE institutions in many parts of the world, but the size of the
HE pie that MOOCs will claim is unknown and will likely be debated
for a long time. Empirical research of the successes and failures
of MOOCs is a promising direction for harnessing their potential
as a source of teaching and learning, and we contribute with an
empirical study from one of the Nordic countries.

MOOC developers have drawn a distinction between xMOOC and connectivist MOOCs
(cMOOCs). In an xMOOC, online courses are built as an extension
of the conventional campus course where the main distinction is
with regards to the number of students who can enrol. Furthermore,
xMOOCs are characterised by the learning resources they provide,
which range from video lectures (a large number of short video tutorials
on related topics), online reading materials, and automated assessment
tools like quizzes (Kesim and Altınpulluk, 2015; Bates, 2014). However,
the first MOOCs were initially envisioned as cMOOCs, a term coined
by George Siemens and Stephen Downes in 2008 (Yuan & Powell,
2013). These initial MOOCs had a decentralised, network-based, nonlinear structure
focused on exploration and conversation rather than fixed content
and instruction (Margaryan, Bianco, & Littlejohn, 2015). In
cMOOCs, each learner is responsible for his or her own learning
process, which is enabled by his or her network of learners and their
connections (Kesim & Altınpulluk, 2015). However, they turned
out to be difficult to organise on the large scale compared to xMOOCs,
which are easier to organise and deliver for a large group of learners.

The differences between the two types of MOOCs are under debate
regarding their respective strengths and weaknesses. A common perception
is that cMOOCs might be preferable from a learning perspective,
while xMOOCs might be more scalable. Another helpful method for
comparing the two types of MOOCs is Sfard’s (1998) acquisition
metaphor (AM) and participation metaphor (PM)
of learning. The AM compares learning to a process of taking in
or being supplied with ready-made knowledge from a more knowledgeable
person through individual efforts, whereas the PM views learning
as a process of taking part in various social practices and shared
activities with fellow learners.

The main aim of this empirical paper is to explore and analyse
the patterns of pedagogical practices and learning experiences in
the first international MOOC offered by the University of Oslo in
2015. It has two research questions:

What are the pedagogical
practices in the MOOC?

What are the expeiriences of the MOOC participants,
and what do they say about the teaching and learning practices in
the MOOC?

The rest of the article is organised as follows: First, we present
a literature review to identify key issues of teaching and learning
in MOOCs, as seen from the AM and PM perspectives. Then we describe
the case and introduces the research design and methods. After that
we present quantitative and qualitative data followed by analyses.
Then we answer the research questions, compare our findings with
the findings reported in the literature, and discuss the possibilities
and limitations of MOOCs in terms of some contemporary trends in online
learning in higher education before we summarise the results of
our research.

Literature review

MOOCs are considered as an upgraded version of distance education
enabled by the advancement of educational technology. Anderson &
Dron (2011) divide distance education pedagogy into three categories:
cognitive behaviourism, social constructivism, and connectivism.
Cognitive behaviourism is defined as the pre-web period of printed
materials, television and radio; social constructivism refers to
the web 1.0 and teleconferences period; and connectivism refers
to the communication and interaction process provided by web 2.0
and social networks. The authors argue that the classical learning
theories are insufficient in that they were developed in an era
in which technology was not as influential on education as it is
today, and they promote connectivism (Anderson & Dron, 2011; Siemens,
2004). The learning process in connectivism takes place as learners
adopt others and share their knowledge through making connections
with the collective knowledge of the community (Siemens, 2004).
Learning is not merely the transfer of knowledge from the teacher
to the learner and does not take place in a single environment;
knowledge is transformed and transferred through the interactions
of people, especially in a web environment (Kop, 2011).

Sfard (1998) argues that the major learning theories are based
upon either the acquisition metaphor or the participation metaphor,
which are not mutually exclusive categories but are complementary
ways of thinking about the complexities of learning. The AM depicts
learning as the acquisition and accumulation of knowledge, inherited
from cognitive models that assume learning is a transmission of
knowledge, and constructivist models that emphasise knowledge is
not passively received but actively built on an individual’s prior
experiences. Knowledge from the AM perspective is considered a ‘commodity’
that can be acquired and therefore applied. Teachers are providers,
facilitators and mediators of teaching and learning. Learners are
consumers and learn by adaptation with the AM. Our preliminary observation
is that the majority of MOOCs are, from the outset, grounded in the
AM, as they are highly structured and solely designed by the teachers
for consuming by a mass of learners. The assessment is more superficial
and automated within a MOOC compared to a conventional campus course,
and feedback on learning activities is minimal and part of summative
rather than formative assessment. MOOCs based on the AM seem to
be suitable for novice learners, as contents are presented in a
carefully planned and sequenced manner (Singh, 2016).

The PM, on the hand, represents learning as an active involvement
in an on-going process of learning together with others in a particular
context. Learning is a process of becoming a contributing member
in a community of learners. Learners enter the MOOC as peripheral
participants and apprentices (Lave & Wenger, 1991) while teachers
and more skilled learners are expert participants and preservers
of a culture of participation (Fischer, 2011). In a nutshell, the
AM focuses on outcome and the PM on process. Thus, Sfard suggests
employing both metaphors in order to design for and understand learning
in modern educational settings.

Paavola, Lipponen & Hakkarainen (2004) and Moen, Mørch &
Paavola (2012) argue that Sfard’s PM is restricted in its focus
on collaborative learning activities and communal participation
and tend to overlook the outcomes of learning. They instead proposed
the knowledge creation perspective (KCM), which emphasises communal
participation of developing shared objects of activity, thus taking
into account both process and outcome (Paavola, Lipponen, &
Hakkarainen, 2004). It is collaborative efforts towards learning
that result in shared knowledge, which is more than the sum of individual
efforts (Moen, Mørch, & Paavola, 2012). The diverse types of
learners from different backgrounds in MOOCs have potentials for
collaborative knowledge creation if their ideas are encouraged, taken
up, synthesised, and applied by individuals.

Kovanovic et al. (2015) found that MOOCs have attracted unprecedented
public involvement and interest compared to previous innovations
in educational technology, but media coverage of MOOCs decreased
by 50% from 2013 to 2014, though government interest in and use
of learning analytics for enhancing MOOC learning
experience are growing (Clow, 2013), and the quality of MOOC discussions
is increasing in the literature. Sunar and colleagues (2015) examined
66 papers related to personalization of MOOCs and
have found that there is a growing trend of researchers focusing
on implementing personalization and adaptation tools in MOOCs to
improve users’ engagement and reduce the huge dropout rate. Researchers
are paying attention to improve individual learning experiences in
MOOCs through personalised learning paths, personalised assessment
through adaptive feedback, personalised forum thread
and personalised learning materials and learning tasks (Andersen
& Ponti, 2014; Sunar et al., 2015). These emerging themes will
be brought up again later in the article when we discuss MOOCs in
terms of contemporary trends in online learning.

In the same way as learning theories over time have created bridges
across the individual and social learning gulf (e.g. as reflected
in the syntheses of AM and PM), learning technologies show a similar
trend, in our context manifest in the debate among xMOOC and cMOOC
camps.

The cMOOC camp emphasises the connectivist approach with co-construction
of knowledge as an integral part of learning (e.g. Andersen &
Ponti, 2014), while xMOOCs advocate a more cognitive-behaviourist
oriented approach with more focus on delivery of information and
individual learning. They determine each a particular pedagogical approach.
The cMOOCs are driven by the principles of pedagogy within a richly
networked setting, aiming toward the social mode of learning, while
xMOOCs are institutionally focused, overtly reliant on video lecture
contents and automated assessment through quizzes, and characterised
by pedagogy short on social contract (Bayne & Ross, 2014).

The recent literature is starting to move away from the simplistic
binary categorization toward more nuanced and micro level discussions
of what is happening in different kinds of MOOCs (Bayne & Ross,
2014). Therefore, some scholars like Waite et al. (2013) have proposed
the notion of ‘hybrid MOOC’ or a process by which educators might
mediate the dichotomy between xMOOCs and cMOOCs (Grunewald et al.,
2013), embodying characteristics of both types of MOOCs, levering
their strengths and inhibiting the weaknesses. However, up until
now MOOCs have not improved the nature of individual learning and have
only changed the form of social learning, yet do not address the
type of learning needed in the 21st century (Bogost, 2013), which
we argue requires the integration of learning theories as well as
learning technologies. Particularly, the xMOOCs largely reproduce the
banking model of education (e.g. Freire, 1970) through readymade
content, including video lectures, digitised resources
and automated assessment (Morris, 2014) and force students to “become
passive, uncritical repository of teacher-owned knowledge” (Hai-Jew, 2014,
p. 341). Pre-packaged instructional material does not promote active
learning (Morris, 2014) and is not necessarily the best way for
everyone to learn (Prensky, 2011). On the other hand, cMOOCs resist
the banking model and provide the students with opportunities to
direct their own learning experiences and to assist peers’ learning
as well (Howard, 2017), but put a very high burden on students to
collaboratively create new understanding, such as co-creation of
tasks (Andersen & Ponti, 2014), which arguably is better tuned
to expert learners than novices, or at least a combination of expert
and novice learners (Moen, Mørch & Paavola, 2012).

In a review of previous studies, Tømte, Fevolden & Aanstad
(2017) have found two contrasting views on the emergence and development
of MOOCs: “the global disruption view and national mediation view”
(p. 211). The proponents of the first view see the MOOCs as innovation
and competition drivers for HE. The proponents of the national mediation view
see MOOCs as e-learning delivery and argue that national education
authorities need to work on policies for adjusting MOOCs into countries’
existing educational systems. This view has emerged as the dominant
in Norway. A government appointed commission for investigating the
possibilities for adopting MOOCs into Norwegian higher education
system found that the pace of digitalisation of HE in Norway has
been slow and argues that MOOCs and new digital technologies can
help develop Norwegian knowledge society. The main motivations for
adopting MOOCs in Norwegian HE context are for strengthening quality,
access, and marketing of Norwegian education and research, increase
recruitment and cooperation, and reduce costs (Tømte et al, 2017).

There are different patterns of learner engagement in MOOCs,
such as active participation, passive participation, lurking, dropping-in,
etc., and these patterns keep changing (Hill, 2013; Milligan, Littlejohn
& Margaryan, 2013). Simon Nelson (2014), CEO of the company
FutureLearn, has characterised learner engagement patterns into
six (overlapping) categories: joiners, learners, active learners,
returning learners, fully participating learners, and social learners.
Morris & Lambe (2014) have categorised MOOC participants into
five types of learners: pre-university learners, university learners,
professional learners, self-directed learners and leisure learners,
according to different types of motivation for taking part in MOOCs.

The multiple ways of categorising MOOC learners can be attributed
to different interpretation of MOOC dropout rates. On average, less
than 10 % of the participants complete the MOOCs (Breslow et al.,
2013; Waks, 2016). There are various reasons for learner dropouts
such as: high workload, challenging course contents, lack of time,
lack of pressure, lack of a sense of community, social influence,
lengthy course start-up, and learning on demand (Hone & El Said,
2016; Zheng et al., 2015). The drop out is partly because of the
“free factor,” which might have attracted learners who wanted to
give it a try, but were not committed to completing the MOOC. In
some cases, learners can buy a certificate by paying for it without
even completing the MOOC (Singh, 2016). However, Clow (2013) argues
that learners’ complete withdrawal from MOOCs may reflect self-directed
learners’ choices to “climb out” (rather than drop out), and this
mirrors learners’ variable level of activity over a MOOC’s duration.
The monolithic distinction between completers and dropout is inadequate
for describing the diversity of learners’ engagement patterns (Clow,
2013; Seaton et al., 2013). Concerning different ways of learning
in MOOCs, Fasihuddin et al. (2015) propose a framework to personalise
open learning environments based on the theory of learning styles,
particularly on Felder and Silverman’s (1988) learning style model.
The framework provides adaptive navigational support through sorting
and hiding the learning materials based on learners’ learning styles
and the involved preferences.

Description of the MOOC

A course titled “What Works: Promising Practices in International
Development” was the maiden MOOC that the University of Oslo offered
through the FutureLearn platform in 2015. It was Norway’s first
online class open to the whole world (Ottersen, 2015). The course
was developed by the University of Oslo’s Centre for Development
and the Environment in close collaboration with Stanford University,
the University of Malawi’s Chancellor College in Malawi, China Agricultural
University in Beijing and the Norwegian Agency for Development Cooperation.
The interdisciplinary researchers, scholars and development specialists
from the collaborating universities and organizations contributed
to video lectures, reading materials, quizzes and so on for the
six-week course. The University of Oslo’s Centre for Information
Technology (USIT) provided technical support in creating and delivering
the MOOC through FutureLearn.

About 7,000 participants from 268 locations throughout the world
signed up for the MOOC. In fact, participants continued to enrol
in the course even after it was over. The majority of the participants
were female (66%). The age group of 26 to 35-years old was the most
prominent (37%). About 49% of the participants were full-time workers,
and 18% were enrolled in full-time education. Most of the participants
(about 81%) had university degrees.

The data extracted from the post-course survey show that more
than 67% of the learners found the structure of the course to be
very clear. For 34% learners, it was fairly clear. Through observation,
it was easy to identify that the course contained different topics related
to developmental studies, including development, governance, and
democracy. The instructors, each coming from one of the collaborating
institutions, provided the various course components, i.e. video
lectures, suggested reading materials, quizzes, discussion/reflection/feedback
forums, one assignment and two videoconferences. Course materials and
activities were delivered weekly so that learners could complete
them as flexibly as possible.

Figure 1.
Dashboard for viewing and navigating the course contents
(top) and weekly course schedule (containing activities
and steps for learning) at bottom.

The MOOC has a dashboard user interface to view and access the
different functions offered (Figure 1): To Do, Activity, Replies
and Progress. The To Do icon was used to navigate course content,
the Activity icon was the archive of the learner’s posts, and Progress showed
how much of the course had been completed. The dates underneath
each week indicated when the course content was delivered on the
platform.

The course was organised by a number of instructors and mentors.
The instructors were university professors and teachers, and international
development specialists, whereas the mentors were master’s students,
a learning designer, a lecturer and a professor who facilitated
the teaching and learning. The instructors did not directly interact
with the learners. Automated quizzes and peer assessments were used
to gauge the understanding and performance of the learners. In
the final week, only one participant who participated on the post-course
survey reported that he peer-reviewed an assessment, whereas others
did not mention it. So, it was hard to determine how many learners
submitted their assessments and received peer reviews. The mentors
notified those who submitted assignments by email after they had
been reviewed. FutureLearn provided a 250-word space for learners
to leave comments and suggestions in response to the assessments.
In addition, there were two online videoconferences offered on the
Talkabout platform.

Data Collection Techniques

The researchers employed a mixed-methods research (MMR) approach
by integrating different methods from two research paradigms: quantitative
and qualitative (Creswell, 2009). In MMR, “the researcher mixes
or combines quantitative and qualitative research techniques, methods,
approaches, concepts or language into a single study” (Johnson & Onwuegbuzie,
2004, pp. 17–18). Pre- and post-course surveys as a source of quantitative data,
and participant observation as a source of qualitative data were
used to explore the pedagogical practices and learners’ experiences
in the MOOC. The design for data mixing that was adopted was the
explanatory or sequential mixed-methods design (Teddlie, 2004; Creswell,
2009). In this design, one type of data (e.g., QUAN) provides a
basis for the collection of another type of data (e.g., QUAL) and
answers one type of question (here, QUAN) by collecting and analysing
two types of data (QUAL and QUAN). Inferences are drawn from the
analysis of both types of data.

The researcher (first author) received access to the quantitative
pre-course survey questions from the USIT first, but the decision
was made to prioritise the qualitative data collection and analysis
despite it being the second phase of the research process. This
decision was influenced by the purpose of the study to explore and
explain pedagogical practices and factors that affected the participants’
engagement in the MOOC. Based upon the pre-course survey questions,
a thematic analysis thematic analysis (Creswell, 2009) of the comments
that participants left on different discussion forums was carried
out. Each comment was coded using a range of analytic concepts and
content descriptors: supportive, critical, expectation, motivating,
demotivating, etc., and as advanced, average, etc., according to different
themes of different questions and carried out in an iterative fashion
(from lower to higher level codes).

The researcher obtained the survey data from the USIT at the
end of the course. The nature of the pre-course survey data was
predictive, while the nature of post-course survey data was descriptive
and explanatory. The themes of the qualitative data were reviewed
following the analysis of the post-course survey data to ensure
that no important theme was overlooked. The number of participants
who responded to the pre-course survey was much higher than the
post-course survey as a result of the high dropout. As stated previously,
qualitative data were used to the quantitative data.

Pre- and Post-Course Surveys

The surveys were developed and delivered by the course provider.
The USIT supplied the researcher with the data. The pre-course survey
data were used to decipher learner demographics in terms of gender,
education level, employment status, participation, expectations, preferred
ways of learning and perceptions. The
post-course survey data were used to explore how learners learned
and what challenges or difficulties they faced during the 6-week
course. Out of the approximately 7,000 course registrants, 936 learners
filled out the pre-course survey, while only 38 replied to the post-course
survey. Other items, like pedagogical practices, course
structure, course design and contents,factors
promoting and hindering learner participation in the course, learners’
preferred ways of learning, learner dropouts, etc., were
drawn from the post-course data. Since there was a significant variation
in the response rate between the two surveys, the data were used
to generate understanding, not for any comparative analysis.

Participant Observation

Participant observation (PO) is “engaging with people in as many
different situations as possible” (Hammersely & Atkinson, 1995,
p. 65). The researcher for this study enrolled in the course and
introduced himself to his peers as an observer of their learning
activities for research purposes. PO helped the researcher gain
an understanding of physical, social, cultural and economic contexts
of the learners. An observation log, which contained a checklist
for coding learners’ comments and views on course structure,
quality and design of course contents, experiences of engagement,
factors promoting and hindering learner participation and nature
of interactions, was used to keep track of observed comments.
The researcher’s role as a moderate participant during the course
changed into a complete observer after the course was over because
of the massive amount of data to comb through. This unobtrusive
and prolonged engagement in the collection of data helped to minimise
bias (Onwuegbuzie & Leech, 2007). The data were observed for
3 months, for approximately 5 hours each week by the first author.

Data and Analysis

Both the survey and observation data focused on recurring themes,
and we identified the following six themes thorough thematic analysis
though thematic analysis (Creswell, 2009) of the data by two researchers:
quality of course design and course content; learner engagement;
expectations of the MOOC; learning preferences; learner dropouts;
nature of interactions among participants. The themes are presented
sequentially, and for each theme first the results of surveys are
presented and then instances of participant observation data provide
supplementary evidence. The two data sets are analysed together
to elaborate the aforementioned themes. When relevant we compare
our findings with findings reported in the literature we have surveyed.

Quality of Course Design and Course Content

Data from the post-course survey showed that the majority of
the learners (76%) found the level of the course to be about right,
about 9% found it a bit advanced, 3% found it to be much too advanced
and 12% found it to be a bit too basic. Concerning course design
and content (Table 1), the majority of the learners liked the course
content, materials, debates, animation videos, etc.

Table 1.
Learners’ perceptions of course design and contents
(N=35)

Data obtained through observation indicated that the majority
of the learners appreciated the course design and course content.
They found them insightful, thought provoking and academically challenging.
However, some learners felt that the content was not explained well,
and a few learners perceived the course content to be propaganda
(i.e., applying a western perspective to solve all issues related
to development). In addition, some learners with hearing impairments
had difficulty understanding the course content because of a lack
of subtitles.

At the end of the course, sixty-six participants left their comments
regarding the course design and contents. Fifty-five participants
felt good about the course. The following statement of P1 explains
how the majority of the participants felt about course design and
contents:

P1: It was not just the content of the course but
also the teaching process that I appreciated. I liked the way that
often we, the learners, were first encouraged to give our views
on some ideas as to what would work before hearing from someone
on the ground who described what had happened and then being given
access to papers with a deep analysis of the issues and the evidence.
I had my prejudices challenged (and even overturned!) by this process.
While there were aspects that I would have liked to know more about,
such as the possibility of development and capacity building even
at a time of war/conflict, I recognize this was a six-week course.
Thank you.

The above statement by P1 indicates that instructors encouraged
the learners to share their views on different topics and issues
and before they hear from someone on the ground how such issues
had been dealt with. Such an approach helped to connect theoretical
ideas with practical experiences and provided learners with insights
into what really works on the ground. Learners’ biases got challenged.
However, some of the issues were less well explained due to time
constraints.

Learner Engagement

Learner engagement in the course was influenced by the student’s
perception of the course content, pedagogical practices, individual
experiences, time, peer group, etc. A larger population of learners
engaged in the discussion/reflection forums than in the forums integrated
with video lectures. This suggests that the participants preferred
learning through reflection and discussion. As indicated by the
post-course survey data, about 57% of the learners spent 30 to 60
minutes on the course each time they participated. The majority
of the learners (about 84%) found the teachers very engaged in the
teaching process. About 78% of the learners had a positive experience,
and only about 6% of the learners found the course to be very poor.

However, the data obtained through observation showed that the
majority of the learners engaged in the discussion/reflection forums,
although learner participation was unevenly spread during the course
period. The data in Table 2 derived from observation of learners’
comments in the different forums show that learner participation
dropped dramatically by week 4 (2/3 along), which is in line with
previous findings (Breslow et al., 2013; Ho et al., 2014; Jordan,
2014).

Table 2.
Learner dropout by number of comments the learners posted
on the forums

The following statements from P6 and P25 are illustrative of
how many participants felt about their engagement with the course.

P6: Thank you very much for the course. I thoroughly
enjoyed participating (albeit late) and appreciate the contributions
of all those involved. You have opened my eyes to new initiatives
and practices that I previously knew nothing about, and also gave
a multitude of perspectives, which helped give more of a 'complete'
view of the situation. Many thanks

P25: Thank you for the course, I have learnt a lot. It wasn't
what I was expecting, I thought it would be videos of case studies
in various countries, as I have experienced in other courses. It
was more academic and more challenging. The production levels were
high and there were some truly superb lectures. The only part I
didn't really enjoy was week 2. I wonder if you lost anyone that
week? I have discovered a prejudice in myself: I would prefer to
have received lectures on democracy from someone from Norway than
someone from USA. I think putting Rule of Law as week two gave it
too much emphasis, part of a week would have been enough for me,
especially as the subject was returned to in week 6. It was also
interesting to read the views and experiences from learners all
over the world, thank you. I enjoyed doing the assignment, though
so far I have only had one review, I hope I will get another. I
enjoyed reading the assignments of others. The interview with Dr
Gro Harlem Brundtland was an uplifting finale.

The quotes of the two participants imply that they thoroughly
enjoyed participating in the course. Some of the learners joined
the course late and found contents more subjective, often biased.
They liked to hear fellow learners’ views and experiences from different
parts of the world. They enjoyed hearing a resource person’s views,
which might have encouraged many of them to continue the course.

The literature indicates that there are different patterns of
learner engagement in different MOOCs: lurkers, drop-ins, passive
participants and active participants (Hill, 2013; Milligan, Littlejohn,
& Margaryan, 2013). Clow (2013) observed four FutureLearn MOOCs
and found seven distinct patterns of learner engagement: samplers,
strong starters, returners, midway dropouts, nearly there, later
completers and keen completers. They noted that these patterns of
engagement were influenced by pedagogical decisions.

Based upon their activities, Nelson (2014) grouped learners on
the FutureLearn platform into six categories: joiners, learners,
active learners, returning learners, fully participating learners,
and social learners. These overlapping categorisations can be simplified into
three main categories, namely joiners, surveyors and social learners,
which we illustrate with our data.

The joiners were the largest category in this
course. Joiners are the subset of those enrolled who actually introduced
themselves to their peers and mentors. The course provider reported
that 7,000 learners signed up for the course, but only 936 responded
to the pre-course survey and actually joined the course and only
955 introduced themselves to their peers and mentors. Some of the
joiners sometimes liked the course content, but did not take active
part in interactions with others.

The surveyors were those who went through all
course content and examined the video lectures and read comments.
If they found something interesting, they engaged in interactions
with peers and mentors; otherwise, they just read the postings.
The number of joiners slowly decreased, which implies that they
became surveyors. Furthermore, when learners joined the course late,
they became surveyors because they were not able to fully understand
the course content. These learners would engage in some activities,
skip some and then come back later.

Finally, the social learners were those who
posted, viewed and learned from comments. The learners who responded
to the post-course surveys (total 38) can be regarded as social learners
because they responded to all questions concerning the course content
and their engagement in the course was high. However, the actual
number of social learners varied according to the different topics
presented in the course. In the first week, about 200 learners engaged
in all content, but this number decreased to about 50 learners in
the last week. These learners also took part in the videoconferences,
wrote blog posts and shared with peers. They also created their
own videos based on their own experiences concerning different issues
of development and poverty reduction.

Expectations from the MOOC

The pre-course data (Table 3) indicate that the majority of the
learners (70%) expected to learn something new, while about 42%
expected to add a fresh perspective to their current work and about
43% expected to improve their career prospects. Similarly, learners
were motivated to join the course to gain extracurricular skills,
to prepare them for further studies, because of the course flexibility,
because they wanted to try online learning, to interact with other
people, etc. The post-course data showed that more than 65% of the
respondents met their expectations of learning flexibly and interacting
with other people. About 56% met their expectation of supplementing
their existing studies. Similarly, the course helped 49% add a fresh
perspective to their current roles and improve their career prospects.
This shows that the expectations from the MOOC were sustained or
increased for those who completed the course.

Table 3.
Learners' expectations of the course (N=936)

Learners with different levels of education, age range, employment
status, etc., had different motivations and expectations for participating
in the MOOC. The following statements from four participants reflect
an attitude that different learners from different background had
different expectations of the course:

P7: Hi there all. I am from South Africa and I am
working for an international NGO focusing on housing solutions.
I am very keen to be exposed to broad perspectives on good practice
that have shown success in different contexts.

P8: Hi everybody. I am from Germany, have a PhD in Medical Research
and work for over 20 years in HealthCare in different disease areas
(currently cardiovascular) on global positions. Non-communicable
diseases are some of the most increasing disease areas – yes, also
in developing countries! Just have a look at: http://rabinmartin.com/report/noncommunicable-diseases-in-the-developing-world-addressing-gaps-in-global-policy-and-research/
And I'm always interested to learn about critical factors, that
make the difference between success and failure!

P10: Hi! My name is … and I'm from Oslo, Norway. I'm a political
scientist who have lived, studied and travelled extensively in southern
Africa. Currently I'm interning for an NGO in Kampala, Uganda –
my first time in east Africa! I'm passionate about some aspects
of international development, however, I'm also extremely critical
of international development aid. I've signed up for this course
to learn more about the subject and to learn about/critically discuss various
approaches.

P12: …I am excited to learn about what really works, and not
at least why it works. I can really see myself work in a NGO (UNICEF,
UNESCO) or Norad after graduation in october this year.

The above statements from different participants and the quantitative
data shown in Table 3 show that different learners had different
expectations of the course.

Morris & Lambe (2014) suggested that expectations vary according
to type of learners, distinguishing among pre-university learners,
university learners, professional learners, self-directed learners,
and leisure learners. The pre-university learners want to increase their
understanding of a current subject; university learners also increase
their understanding of a current subject and explore potential areas
for further study. Professional learners want to gain competences
and skills to improve their career prospects, and add fresh perspectives
to their current work. Self-directed learners want to gain knowledge
and understanding of new subject areas, or build and expand a professional
network based on personal interest. The leisure learners want to
satisfy their curiosity and support the professional community.

Learning Preferences

Learning preferences refer to an individual learner’s habitual
ways of processing and acquiring information, and data from learning
preferences are shown in Table 4.

Data from the surveys show that the majority of learners preferred
learning by watching video lectures and taking quizzes. Around 50%
of the learners liked to learn by reading the comments posted by
fellow learners, by following links to other related contents, and
by discussing matters online with fellow learners.

Personal comments indicate in more detail what preferences learners
had regarding learning, which include the role of collaboration
and reading commentaries of videos for learning, as shown in the
following online conversation by three participants.

P23: Thank you so much all of classmates who collaborated
to improve my knowledge. It is greatly appreciated.

P24: would be great if all the videos have translations/word
version. nice lessons. just wondering how citizen fora has worked
in other developing countries especially ….

P29: http://blog.riverford.co.uk/2015/03/06/guys-newsletter-unruly-cabbages-the-last-stand/
…, you may find this blog on seeds, from an English organic farmer,
interesting.

As indicated by the above statements, the learners engaged in
a wide variety of participatory activities such as knowledge sharing,
commenting on video lectures, posting counter arguments on fellow
learners’ views and perspectives, sharing their views through their personal
blogs, reading transcripts, reading suggested reading materials,
etc. Such activities promoted active and collaborative learning
practices in the MOOC.

There were different ways for the participants to learn in the
MOOC. Watching videos or reading the related transcripts was the
only way for acquiring the actual information from the course. In
addition, there was a separate forum for reflection activities,
where learners were encouraged to create their own blog posts and
videos and share them with peers.

Felder and Silverman’s (1988) categorization of learners on the
basis of how they process and acquire information proposes four
types of learning preferences: sensory or intuitive; visual or auditory;
active or reflective, and sequential or global. Sensory learners
prefer learning by example and practice, while intuitive learners
prefer meaning and theories; visual learners learn through pictures,
diagrams, and films, while auditory learners prefer learning by
written and spoken explanations; active learners prefer to work
with others and create things, while reflective learners prefer
thinking and working alone; and sequential learners prefer learning
in an orderly and linear manner, while global learners prefer to learn
holistically. From our data we can say that learners who preferred
to watch videos and read the related transcripts can be termed visual-auditory
learners or sequential-holistic learners. The learners who prefer
to engage with peers and mentors in the discussion forums can be
termed as active-reflective learners.

Learner Dropouts

A few learners responded to the post-course survey question on
what factors hindered them from participating in the course. They
could choose from lack of time, lack of motivation/interest, lack
of pace as the course progressed, difficulty in using the platform,
different learning environment, poor internet connection, and joining
the course just for curiosity.

The following statements of three different participants indicate
different contributing factors for learner dropouts:

P3: (an English teacher): …I think there are two
factors behind that. Firstly, some parts of the course especially
week1 and some of the …Chinese contributions were perceived by many
as propaganda … I think it alienated quite a lot of students. In
future the tone of some lectures could be softened.

Secondly, language has been a barrier. The lectures have been
longer, denser and linguistically far more demanding than other
FutureLearn courses I have done. Personally, I appreciate the extra
rigor and have got a lot out of this course. But I think the team
overestimated the English level of many students. In one of the
assignments I reviewed the writer was completely out of his depth
with the topic in English and so was one of those who reviewed my
article. I[n] future it might help to include subtitles in the videos
or connect the comments forums to a translation website so that
people could write in their native language if necessary

P16: For me, not having a transcript is more than an inconvenience.
My hearing is not good so this possibly amounts to discrimination.
I have completed several of these Future Learn courses but I've
never met with a straight, though apologetic 'no' before. Transcripts
might have been late in coming but they came eventually. This is
a great disappointment.

P7: Hello, my internet connection is not the best I would love
you attach the transcript of each video so that we can download
and read in case of poor internet connection

Through observation, three other reasons were also found, namely
internet quality, lack of time and a lack of transcripts for some
of the lecture videos. For a few participants, an important factor
hindering their participation was a lack of English language proficiency. These
learners asked for the transcripts for each video, and the mentors
tried their best to supply these transcripts as fast as possible.
When there was a delay, fellow learners also made transcripts for
some of the videos and shared them with their peers. The fact that
the course was free may have also contributed to dropout because
the learners were not fully invested in completing the course.

Many of these reasons for dropout have been noted in previous
research (Hone & El Said, 2016; Zheng et al., 2015). However,
dropping out should be viewed as just one of many activities that
self-directed learners engage in (Clow, 2013). The monolithic distinction
between completers and dropout is inadequate for describing the
diversity of learners’ engagement patterns (Clow, 2013; Seaton et
al., 2013), and the dropouts may have already achieved their aim
of learning about a particular concept before they completed all
parts of the course. They may just have been surveyors of the course
contents.

Nature of Interactions Among Participants

The post-course survey data showed that the majority of the learners
(84%) found the mentors to be very engaging. Through observation
it was found that only mentors and learners took part in the comment/discussion/reflection/feedback
forums, not the instructors. The observed interactions were between
mentors and learners, and between learners and learners. The mentors
would read the learners’ posts and then post replies. Their role
was to balance the viewpoints among participants. Interactions between
learners were much more frequent than between learners and mentors.
The mentors tried to motivate the learners to watch the videos,
read the suggested material, take quizzes and interact with fellow
learners. Fellow learners answered many of the other learners’ questions
in the discussion forums. As stated previously, learners even provided
English subtitles to some of the video lectures. As the course progressed,
the instructors seemed to be out of touch with the learners’ activities
as they only appeared on the lecture videos and videoconferences.
This can be compared to the idea in scaffolding of a teacher fading away
from the educational activities as the learners gradually become
independent. The lack of actively engaged teachers in the whole
learning process—what we take for granted in conventional teaching—may
have actually discouraged some of the learners from remaining in
the course. On the other hand, the learner community provided an
alternative, which we present next.

Discussion forums integrated with each section of the course
were the main tools for interacting, and hence learning, during
the MOOC. Interaction was supported both synchronously and asynchronously:
the host organised videoconferences and the conversations in the
discussion forums were asynchronous. The learners engaged intensively
in asynchronous conversations and made use of social networking
services outside of the platform, such as Facebook and Twitter,
to share content to self-organise the required scaffolding. This
can be seen as a process of collaborative learning (Ludvigsen &
Mørch, 2010), which was one of the aims of running the MOOC. Future
work should explore how to best stimulate collaborative learning
on a broader scale, and we discuss some of the issues related to
this in the next section.

General Discussion

In this section we answer and discuss our research questions,
which have two parts, pedagogical practices and learners’ experiences
from the MOOC. In addition, we identify some emergent trends in
technology development with implications for MOOCs, and we discuss alternative
directions MOOCs can take in future higher education.

Pedagogical Practices

Five key pedagogical features characterise the MOOC we have studied:
video lectures, reading materials, e-assessment, discussion forums
and videoconferences. The proper sequence was first to provide the
contents of teaching and learning to the participants and then encourage
them to discuss the materials by collaborating with peers. The
course structure, course content and learning activities in the
MOOC were solely designed and created by the instructors in advance.
The video lectures and reading materials suggested by the instructors
were the primary sources of knowledge, and discussion forums were
the major sources of interaction and collaborative learning. The
task of interacting with students was left to the mentors who explained
concepts, clarified misconceptions, and helped learners acquire
knowledge. Therefore, the MOOC resembled both an xMOOC and a cMOOC,
but it was found to be much closer to an xMOOC than a cMOOC. The
concepts of the banking model of teaching (Freire, 1970) and the
acquisition metaphor of learning (Sfard, 1998) can partly explain
this; they are based on the idea that the human brain is a container
and the learning process fills the container with content. The course
included video lectures, reading material and peer comments for
accumulating facts and acquiring knowledge. The video lectures were
the primary method of transmitting information, and the automated
quizzes were the main tool for assessment. Thus, the MOOC was acquisition
oriented at the outset, as the instructors’ role was to develop
and deliver highly structured course content.

However, the learners did enjoy the video lectures, which suggests
that they wanted to acquire as much knowledge as possible. They
became consumers of the knowledge communicated through the platform.
Automated quizzes assessed the basic facts, such as ‘Income inequality
has been increasing in Latin America since 2002’ (True or False)’.
The whole process was directed towards helping the learners acquire
as much knowledge as possible about what works in international
development programs. Some researchers argue that even though videos
can be watched multiple times at the learner’s own pace, it is not
necessarily the best way for every person to learn (Prensky, 2011),
and pre-packaged instructional content does not promote active learning
(Morris, 2014). In a very large MOOC with thousands of participants,
it is hard to pay attention to the individual needs, and a reliance
on automated testing will likely push MOOC providers further into
the banking model of education and force students to ‘become passive,
uncritical repository of teacher-owned knowledge’ (Hai-Jew, 2014,
p. 341). This increases the “danger of the relegation of education
to a mere exercise of technology” (Freire, 1970, p. 75). However,
technology also provides new solutions to the shortcomings associated
with very large MOOCs, which have many participants with individual
needs. We address this later.

Learners’ Experiences of Participation

The MOOC brought a global learner cohort together for information
or knowledge sharing, connection and interaction, and created opportunities
for collaborative learning through discussion forums. A large number
of learners engaged in the forums, which were the only method used
to activate the learners in the course content, apart from two videoconferences
stimulating to debate. The discussion forums were the spaces and
tools that brought geographically scattered learners together and
encouraged them to build a community of learners and a culture of
participation (Fischer, 2011). The interactions that took place
in the forums were asynchronous, so the learners had more time for
flexible communication, e.g. thinking about what to say compared
to face-to-face interactions. The forums were also the only way
for promoting collaborative learning practices (Ludvigsen &
Mørch, 2010).

However, synchronous communication by two videoconferences complemented
the discussion forums and helped learners directly discuss the issues
with the mentors and fellow learners. This whole process can be
seen as an attempt at enculturation into a community of
practice (Lave & Wenger, 1991; Wegner & Nückles,
2015), but, as discussed below, there was a high dropout rate in
this course, which indicates that for some, the MOOC was more of
a community of interest (Fischer, 2001), which
consists of people who come from different communities of practice
(e.g., different professions) and who may not want to complete a
course or become a skilled practitioner in a field, but rather want
to gain knowledge about one or more sub-themes of the course that
are of particular interest (Fischer, 2001) in order to promote a
self-directed type of learning (Clow, 2013; Morris & Lambe,
2014).

In these online communities, newcomers often enrol without long-term
expectations; for example, they might want to find the answer to
a question or the solution to a problem, and once they have achieved
this goal, they leave the community. A community of interest is
therefore an assembly of people brought together to exchange critical
information, obtain answers to personal questions or problems, to
improve their understanding of a subject, to share common passions
or to engage in a hobby or activity (Fischer, 2001). Thus, the MOOC
seemed to enrol members in a community of practice as well as multiple
communities of interest. Further work ought to study this preliminary
hypothesis in more detail.

The High Dropout Rates

The MOOC in this study had a high dropout rate. The data show
that the main causes for the steep dropout rate were lack of time,
lack of motivation or interests, poor internet quality, lack of
proficiency in English, some of the course contents being perceived
as western propaganda, and dense or fuzzy videos. The course may
not have catered to the needs of a diverse group of learners, but
learner completion and dropout rates need to be seen as a part of
a process of becoming social learners. The learners’ withdrawal
from the MOOC may reflect a self-directed choice to climb out (rather
than dropout), which mirrors these learners’ varying levels of participation
in the MOOC (Clow, 2013). In addition, the kind of pedagogical practices
prevalent in the MOOC, which were more in line with the AM than the
PM, did not seem to promote learner-centred practices.

Approaches belonging to the PM typically emphasise communities,
social practices, collaborative activities and the situated nature
of human cognition and knowledge. FutureLearn’s approach of bringing
together different institutions, scholars and experts from all over
the world to develop and deliver course content may result in enhanced
institutional and teacher collaboration and community building among
teachers. However, whether such online courses can also help learners
build a community remains to be seen.

Connecting, interacting and sharing across diverse cultures (Fischer,
2011), attitudes and skill sets in a MOOC (McAuley et al., 2010)
may not necessarily promote collaborative learning, as learners
from diverse locations and cultures may not feel ready for collaboration.
Therefore, course organisers should clearly state the aim of enculturation,
namely, for students to progress from novice and peripheral participants
to advanced practitioners in a community of practice (Lave &
Wenger, 1991), or to help professionals find answers to specific
problems by participating in a community of interest (Fischer, 2001).

The KCM

Paavola & Hakkarainen (2005) and Moen, Mørch & Paavola
(2012) argue that Sfard’s (1998) AM and PM have limitations because
they only represent the monological and dialogical approaches to
knowledge and learning and lack the ‘trialogical’ approach, which refers
to “learning as a process of knowledge creation which concentrates
on mediated processes where common objects of activity are developed
collaboratively” (Paavola & Hakkarainen, 2005, p. 535). The
trialogical approach and KCM focuses on understanding the processes
of collective knowledge advancement that are important in a knowledge
society. This metaphor goes beyond the two basic metaphors (AM and
PM). It posits that individuals participate in collaborative learning
activities in a community of learners, which allows them, in some
situations, to acquire individual knowledge and, in other situations, to
create new knowledge that is usable for the community at large (Moen,
Mørch, & Paavola, 2012). Learners in this MOOC were encouraged
to create their own videos and post them on the discussion forum.
They were also told to write their own blog posts and share them
with fellow learners. However, these were individual efforts rather
than collaborative group work because the responses to students’
creations (videos and blogs) were few and not meant for engaging
in collaborative knowledge creation. This indicates an area for
further work—promoting collaborative knowledge creation in MOOCs
through sustained efforts at building on each other’s videos and
blog posts.

MOOCs and Trends in Online Learning

Four trends in technology development in online learning address
some of the shortcomings of MOOCs cited above: learning analytics;
formative assessment by new forms of feedback; personalization,
and collaboration support. They can help to increase collaboration,
stimulate sustained engagement, suggest new models of course preparation,
detecting dropout and providing countermeasures, while leveraging
strengths such as flexibility of learning and scaling up delivery
of instructional material.

Learning analytics (LA) is a new interdisciplinary
field that takes advantage of learning activities captured and stored
within digital learning environments such as MOOCs and can ‘mine’
and analyze these digital traces (log data) to identify patterns
of learning behaviour and provide insights into learning practices
(Gašević, Dawson & Siemens, 2015), including identifying potential
dropouts of a course based on predictive modelling. By using visualization
techniques, LA can provide instructors and mentors with overviews
of learners’ activities with educational resources in large online
communities to help them cope with management issues as enrolment
arises. Social learning analytics can visualise communication links
between participants in collaborative learning activities, identify outliers
in a community, and measure collaborative activity using social
network analysis (Ferguson & Shum, 2012).

Formative assessment by new forms of feedback is
found to be particularly effective in promoting learning, because
good feedback encourages evaluation of an educational activity and
provides information on both teaching and learning (Black &
William, 2009; Gamlem & Smith, 2013). However, formative assessment
is a thorny issue in MOOCs because it takes a long time for a small
group of teachers to provide individualised feedback in a large
community. Alternative methods have been proposed, such as peer
feedback and adaptive (automated) feedback. Peer feedback was observed
in our study through self-organised scaffolding, but to the best
of our knowledge it was not organised as such by the course organisers.
To improve students’ learning further, teachers and educational
technologies will need to embed feedback much more actively in learning
activities. Data generated through learning activities such as solving
a quiz to determine prior knowledge and writing an essay to demonstrate
new skills according to a learning goal are prime data sources for
adaptive feedback systems (Engeness & Mørch, 2016).

Personalization is a research focus in order
to improve users’ engagement and to reduce huge dropout rates (Sunar
et al., 2015). A promising direction in personalization research is
personalised learning materials and learning tasks. Andersen &
Ponti (2014) investigated participants’ co-creation of tasks in
cMOOCs and what opportunities and challenges emerge. The authors
identified and studied how peers can be part of creating course
content and suggest offloading some of the teachers’ work in course
preparation onto students by co-creating course assignments, which
they refer to as mutual development of tasks (Andersen & Ponti,
2014).

Collaboration support is another solution to
making learning more engaging, as computer supported collaborative
learning can support 21st century skills (Ludvigsen &
Mørch, 2010). Furthermore, when asynchronous technology is supplemented
by synchronous technology beyond video conferencing, new forms of
learning environments that can stimulate sustained engagement become
possible. This includes 3D virtual worlds, virtual reality (VR)
and augmented reality (AR) (Caruso, Mørch, Thomassen, Hartley, &
Ludlow, 2014). We expect in the future to see hybrid cMOOCs, which
support both modes of interaction with fellow learners, teachers
and instructional materials, where individual learners are switching
between synchronous and asynchronous modes of interaction according
to small group preferences.

Role of MOOCs in Higher Education

MOOCs can bring global learner cohorts together for information
or knowledge sharing, connection and interaction, and open up opportunities
to foster directed learning. Additionally, MOOCs can be useful digital
resources for referential learning, and promote a lifelong learning
culture by extending the reach and access to educational opportunities.
Furthermore, they can bring different higher education institutions
together from all over the world, with different scholars and experts
for delivering the course contents, which can strengthen institutional
collaboration for innovating online pedagogy and learning activities.
Collaboration among different institutions and instructors also
contributes to new forms of researcher exchanges and effective development
of teachers’ dispositions, knowledge and skills, which in turn may
result in creation of better teaching and learning materials.

In addition, Yuan & Powell (2013) argue that MOOCs can positively
impact HE in two different ways: “improving teaching; and encouraging
institutions to develop distinctive missions that will include considerations
about openness and access for different groups of students” (pp.17–18).
However, video-based learning in the MOOC, which characterises xMOOCs,
may not result in meaningful learning (Morris, 2014) because the
current format of MOOCs promotes the banking model of education,
which might be suitable for learning in the knowledge domain, which
can be mastered through repetitive practice as in many courses in
undergraduate education. Thus, we may see in the future a branching
in HE among institutions that focus on distance education and courses
delivered as MOOCs for lower degree students, and institutions that
focus on graduate education in residential research based universities.
They can be useful tools to connect HE institutions with workplaces
as more than fifty percent of the MOOC participants are practitioners,
which can augment the process of information and knowledge sharing
between HEIs and workplaces.

Summary and Conclusions

In this article we have reported findings from the first International
MOOC organised at the University of Oslo in 2015. This MOOC consisted
of video lectures on contemporary topics (best practices) in international
development, online reading material, e-assessment (quizzes), discussion
forums, and video conferencing. These components have long been used
in distance education, and the course was presented in a similar
manner to on-campus courses. What was unique to this MOOC compared
to distance education and on-campus courses was the large numbers
of students who initially enrolled. This MOOC was similar to an
xMOOC in the sense that teachers had a privileged role in designing
and determining the course content and the teaching and learning
processes. In contrast, the FutureLearn platform is said to be a
learner-centred MOOC, but our findings indicate it was teacher-centred
in this case, as it was the teachers who designed everything that
happened on the course. It is therefore mainly an xMOOC, but the
asynchronous textual exchanges were the main form of online communication
in the course and they supported the participation metaphor (PM)
of learning, but were not sufficient to help learners become actively
engaged in their own learning. A large portion of the learners liked
the course contents and teaching process, and on the basis of their
learning activities, we found three categories of learners: joiners,
surveyors, and social learners. However, some found some of the
course materials to be biased and subjective, which was one of the
reasons for the high dropout rates. Among the social learners we
observed a phenomenon that can be explained as an emergent form
of PM, approaching the collaborative knowledge creation metaphor.
The teachers did not engage in interactions with learners, only
the mentors appointed by the course providers did. In lack of teacher
support, the learners depended upon peer support for scaffolding
their learning and a group of learners emerged that took on this
task, which is one of the most interesting findings from the study.
This was realised through self-organised scaffolding activities:
making videos of their experiences, writing blogs and engaging in
the debates in the discussion forums. A direction for further research
is to explore whether or not MOOCs can promote learning activities
that leverage contemporary research in learning analytics, adaptive
learning, formative assessment, and collaboration support to achieve
better integration of individual and collaborative learning within
an environment that is engaging and manageable for both learners
and teachers.

Acknowledgements

The authors are grateful to Jesper Havrevold, USIT, University
of Oslo, for providing the authors with quantitative data and giving
the first author access as participant observer in the “What works”
MOOC.

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